Search Results - (( parameter optimization search algorithm ) OR ( parameter optimisation system algorithm ))
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Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm
Published 2018“…However, to fully utilize the algorithm, the parameter of the algorithm need to be set properly. …”
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Monograph -
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Performance Comparison of Particle Swarm Optimization and Gravitational Search Algorithm to the Designed of Controller for Nonlinear System
Published 2014“…This paper presents backstepping controller design for tracking purpose of nonlinear system. Since the performance of the designed controller depends on the value of control parameters, gravitational search algorithm (GSA) and particle swarm optimization(PSO) techniques are used to optimise these parameters in order to achieve a predefined system performance. …”
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A comparative evaluation of PID-based optimisation controller algorithms for DC motor
Published 2023“…Controllers; DC motors; Electric control equipment; Particle swarm optimization (PSO); Proportional control systems; Three term control systems; Two term control systems; Backtracking search algorithms; Comparative analysis; Comparative evaluations; Controller algorithm; Industrial activities; Optimum parameters; Particle swarm optimisation; Proportional integral derivative controllers; Electric machine control…”
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ANFIS modelling of a twin rotor system using particle swarm optimisation and RLS
Published 2010“…The antecedent parameters of the ANFIS are optimized by a PSO algorithm and the consequent parameters are updated using recursive least squares (RLS). …”
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Proceeding Paper -
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Adaptive Spiral Dynamics Metaheuristic Algorithm for Global Optimisation with Application to Modelling of a Flexible System
Published 2016“…A linear parametric modelling approach is utilised with an autoregressive model with exogenous inputs (ARX) structure for a flexible system. The proposed algorithm is then used to optimise parameters of the ARX structure. …”
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Investigation of Meta-heuristics Algorithms in ANN Streamflow Forecasting
Published 2024“…In the latter, parameter tuning utilizing the design of experiment (DOE) technique, has become an integral element in the optimization process due to reliance on their parameters. …”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Hence, the algorithm must overcome the problem of dynamic updates in the internal parameters or counter the concept drift. …”
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Thesis -
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Plant leaf recognition algorithm using ant colony-based feature extraction technique
Published 2013“…Then, based on the characteristics of each species, decision making is done by means of ant colony optimisation as a search algorithm to return the optimal subset of features regarding the related species. …”
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Optimization and assessment of substation grounding grid designs in non-homogeneous soil conditions
Published 2023“…An optimisation method established from the Simulated Annealing (SA) algorithm is applied to search for an optimal grounding design solution. …”
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Cuckoo optimised 2DOF controllers for stabilising the frequency changes in restructured power system with wind-hydro units
Published 2021“…Different types of metaheuristic optimisation methods like teaching–learning-based optimisation (TLBO) and cuckoo search algorithms are suggested to acquire the optimal gain values of the proposed controllers. …”
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Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia
Published 2019“…Spearman Correlation was used to checked multi-collinearity effect on debris flow conditioning factors; evaluations factors of Information Value (IV), Crammer V were assessed.Wrapper feature subset selection technique was used, different metaheuristic search algorithms (e.g. Cuckoo search), and evaluator or model inducing algorithms (e.g SVM) were utilized for feature subset selection, which further compared to select the optimal conditioning factors subset. …”
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Recent Development of Grid-Connected Microgrid Scheduling Controllers for Sustainable Energy: A Bibliometric Analysis and Future Directions
Published 2025“…This study presents a comprehensive bibliometric analysis of grid-connected microgrid (MG) scheduling controller techniques. An extensive search was done in the Scopus database using preset parameters to extract articles relating to the MG scheduling controller. …”
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A Study On The Application Of Gravitational Search Algorithm In Optimizing Stereo Matching Algorithm’s Parameters For Star Fruit Inspection System
Published 2018“…Benchmarking has done by comparing the result obtained with the previous literature that implements Particle Swarm Optimization. The result indicates that the application of Gravitational Search Algorithm as parameters tuner for stereo matching’s parameters tuning is essentially on par with the Particle Swarm Optimization Algorithm.…”
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Heterogenous adaptive ant colony optimization with 3-opt local search for the travelling salesman problem
Published 2020“…The majority of optimization algorithms require proper parameter tuning to achieve the best performance. …”
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A Hybrid Least Squares Support Vector Machine with Bat and Cuckoo Search Algorithms for Time Series Forecasting
Published 2020“…However, its operation relies on two important parameters (regularization and kernel). Pre-determining the values of parameters will affect the results of the forecasting model; hence, to find the optimal value of these parameters, this study investigates the adaptation of Bat and Cuckoo Search algorithms to optimize LSSVM parameters. …”
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…The proposed method combined the improved teaching-learning-based optimisation (ITLBO) algorithm, improved parallel JAYA (IPJAYA) algorithm, and support vector machine. …”
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An Improved Hybrid of Particle Swarm Optimization and the Gravitational Search Algorithm to Produce a Kinetic Parameter Estimation of Aspartate Biochemical Pathways
Published 2017“…The results show that the proposed algorithm outperformed other standard optimization algorithms in terms of accuracy and near-optimal kinetic parameter estimation. …”
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Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis
Published 2018“…In this paper, three optimization algorithms which are particle swarm optimization (PSO), gravitational search, and Sine Cosine algorithms are employed to optimize the grinding process parameters that may either reduce the cost, increase the productivity or obtain the finest surface finish and resulting a higher grinding process performance. …”
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